ABSTRAKSI: Kata Kunci : ABSTRACT: At this moment traffic jams are a scourge to all people, especially for those who live in big cities such as Bandung. Traffic jams made the activities of many people hampered and inevitably there must be a solution to avoid the problem. One of the applicable solutions is an earlier information of traffic jam, therefore people can avoid traffic jam. To create this, it requires a system that can identify the density of traffic situations.
In this final task, information system of traffic jam is made which is in implementation used wavelet method as a feature extraction and support vector machine as classifier. Furthermore the research on system accuracy that for recognizing the condition of heavy traffic, medium, or black has been done. Moreover an analysis on what factors that affect the accuracy of support vector machine methods has been done too.
Based on the observations that have been done, the resulting accuracy showed good results that is 92,22% for classification on traffic conditions.Keyword: Traffic density, Haar Wavelet, Support Vector Machine (SVM)